Example usage for com.google.common.util.concurrent AtomicLongMap asMap

Introduction

In this page you can find the example usage for com.google.common.util.concurrent AtomicLongMap asMap.

Prototype

Map asMap

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Usage

From source file:co.mitro.core.util.RpcLogReader.java

public static void main(String[] args) throws IOException {
    AtomicLongMap<String> counter = AtomicLongMap.<String>create();
    Map<String, Span> txnLength = new HashMap<>();
    Span duration = new Span();

    for (int i = 0; i < args.length; ++i) {
        String filename = args[i];
        System.err.println("Reading file: " + filename);
        JsonRecordReader rr = JsonRecordReader.MakeFromFilename(filename);
        JsonRecordReader.JsonLog log;/*from w w w .ja va 2 s  .  c o m*/
        try {
            while (null != (log = rr.readJson())) {
                counter.incrementAndGet(log.metadata.endpoint);
                duration.addTime(log.metadata.timestamp);
                if (log.metadata.endpoint.endsWith("BeignTransaction")
                        || log.payload.implicitBeginTransaction) {
                    txnLength.put((String) ((Map) log.metadata.response).get("transactionId"),
                            new Span(log.metadata.timestamp));
                } else if (!Strings.isNullOrEmpty(log.payload.transactionId)) {
                    txnLength.get(log.payload.transactionId).addTime(log.metadata.timestamp);
                }
            }
        } catch (EOFException e) {
            System.err.println("unexpected end of file; skipping");
        }
    }
    System.out.println("total duration: " + duration.duration());
    for (String k : counter.asMap().keySet()) {
        System.out.println(k + ": " + counter.get(k));
    }
    List<Long> times = new ArrayList<>();

    for (Span s : txnLength.values()) {
        times.add(s.duration());
    }
    Collections.sort(times);
    double meanTime = 0;
    for (Long l : times) {
        meanTime += l;
    }

    meanTime /= txnLength.size();
    double stdDev = 0;
    for (Long l : times) {
        stdDev += Math.pow((l - meanTime), 2);
    }
    stdDev /= txnLength.size();
    stdDev = Math.pow(stdDev, 0.5);

    // percentiles
    long PERCENTILES = 10;
    for (int i = 0; i <= PERCENTILES; i += 1) {
        System.out.println("percentile " + i * PERCENTILES + ": "
                + times.get((int) ((times.size() - 1) * i / PERCENTILES)));
    }

    System.out.println("write txns:");
    System.out.println("num: " + txnLength.size() + ", mean:" + meanTime + ", stddev:" + stdDev);

}

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From source file:com.navercorp.pinpoint.collector.util.AtomicLongMapUtils.java

public static <T> Map<T, Long> remove(AtomicLongMap<T> atomicLongMap) {
    final Map<T, Long> view = atomicLongMap.asMap();

    // view.size() is not recommended, cache entry is striped and volatile field
    final List<T> keySnapshot = keySnapshot(view);

    return remove(atomicLongMap, keySnapshot);
}

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From source file:com.cloudera.oryx.app.mllib.rdf.RDFUpdate.java

private static AtomicLongMap<Integer> merge(AtomicLongMap<Integer> a, AtomicLongMap<Integer> b) {
    for (Map.Entry<Integer, Long> e : b.asMap().entrySet()) {
        a.addAndGet(e.getKey(), e.getValue());
    }/*from w  w w  . ja  v  a  2  s .  c o m*/
    return a;
}

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From source file:com.cloudera.oryx.app.mllib.rdf.RDFUpdate.java

/**
 * @param trainPointData data to run down trees
 * @param model random decision forest model to count on
 * @return maps of node IDs to the count of training examples that reached that node, one
 *  per tree in the model//from   w  ww.  j a  v a2  s  . c  om
 * @see #predictorExampleCounts(JavaRDD,RandomForestModel)
 */
private static List<Map<Integer, Long>> treeNodeExampleCounts(JavaRDD<LabeledPoint> trainPointData,
        final RandomForestModel model) {
    List<AtomicLongMap<Integer>> maps = trainPointData
            .mapPartitions(new FlatMapFunction<Iterator<LabeledPoint>, List<AtomicLongMap<Integer>>>() {
                @Override
                public Iterable<List<AtomicLongMap<Integer>>> call(Iterator<LabeledPoint> data) {
                    DecisionTreeModel[] trees = model.trees();
                    int numTrees = trees.length;
                    List<AtomicLongMap<Integer>> treeNodeIDCounts = new ArrayList<>(numTrees);
                    for (int i = 0; i < numTrees; i++) {
                        treeNodeIDCounts.add(AtomicLongMap.<Integer>create());
                    }
                    while (data.hasNext()) {
                        LabeledPoint datum = data.next();
                        double[] featureVector = datum.features().toArray();
                        for (int i = 0; i < trees.length; i++) {
                            DecisionTreeModel tree = trees[i];
                            AtomicLongMap<Integer> nodeIDCount = treeNodeIDCounts.get(i);
                            org.apache.spark.mllib.tree.model.Node node = tree.topNode();
                            // This logic cloned from Node.predict:
                            while (!node.isLeaf()) {
                                // Count node ID
                                nodeIDCount.incrementAndGet(node.id());
                                Split split = node.split().get();
                                int featureIndex = split.feature();
                                node = nextNode(featureVector, node, split, featureIndex);
                            }
                            nodeIDCount.incrementAndGet(node.id());
                        }
                    }
                    return Collections.singleton(treeNodeIDCounts);
                }
            })
            .reduce(new Function2<List<AtomicLongMap<Integer>>, List<AtomicLongMap<Integer>>, List<AtomicLongMap<Integer>>>() {
                @Override
                public List<AtomicLongMap<Integer>> call(List<AtomicLongMap<Integer>> a,
                        List<AtomicLongMap<Integer>> b) {
                    Preconditions.checkArgument(a.size() == b.size());
                    for (int i = 0; i < a.size(); i++) {
                        merge(a.get(i), b.get(i));
                    }
                    return a;
                }
            });

    List<Map<Integer, Long>> result = new ArrayList<>(maps.size());
    for (AtomicLongMap<Integer> map : maps) {
        result.add(map.asMap());
    }
    return result;
}

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From source file:org.nanoframework.commons.support.logging.AbstractAnalysisLogger.java

protected long total(final AtomicLongMap<String> analysis) {
    if (analysis == null || analysis.isEmpty()) {
        return 0;
    }/*w ww.  j  av  a  2  s.  c o  m*/

    final AtomicLong total = new AtomicLong(0);
    analysis.asMap().values().forEach(count -> total.addAndGet(count));
    return total.get();
}

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